Paper Citation Record · LEDGER

MDD-LLM: Towards Accuracy Large Language Models for Major Depressive Disorder Diagnosis

As of 23 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2505.00032.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2505.00032 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:53:11.946247Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

34 of 34 outbound references displayed

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verified fuzzy33
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9cd99937-1b40-4de3-b08f-5febf6151250 · outbound

This paper cites Comorbid depression in medical diseases.

MDD-LLM: Towards Accuracy Large Language Models for Major Depressive Disorder Diagnosis Comorbid depression in medical diseases

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:53:12.317989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation b7aaeeb5-64b5-49ec-a834-2d7afc75953a · outbound

This paper cites Major depressive disorder: hypothesis, mechanism, prevention and treatment.

MDD-LLM: Towards Accuracy Large Language Models for Major Depressive Disorder Diagnosis Major depressive disorder: hypothesis, mechanism, prevention and treatment

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:53:12.308020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 89ce101f-0c5a-48d1-a937-a4e268dbca6a · outbound

This paper cites Despite the substantial resources allocated to researching the causes, diagnosis, and treatment of MDD, progress in these areas remains below expectations.

MDD-LLM: Towards Accuracy Large Language Models for Major Depressive Disorder Diagnosis Despite the substantial resources allocated to researching the causes, diagnosis, and treatment of MDD, progress in these areas remains below expectations

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:53:12.348757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0283ecc5-fafc-47ba-9b0b-e53b1f4a42d5 · outbound

This paper cites Combined prevention for substance use, depression, and anxiety in adolescence: a cluster-randomised controlled trial of a digital online intervention.

MDD-LLM: Towards Accuracy Large Language Models for Major Depressive Disorder Diagnosis Combined prevention for substance use, depression, and anxiety in adolescence: a cluster-randomised controlled trial of a digital online intervention

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:53:12.276451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 1cab5da0-8b03-4a75-b888-20002ca5a159 · outbound

This paper cites To our knowledge, the proposed MDD-LLM is the first LLM-based solution fine-tuned on an extensive real-world dataset for MDD diagnosis.

MDD-LLM: Towards Accuracy Large Language Models for Major Depressive Disorder Diagnosis To our knowledge, the proposed MDD-LLM is the first LLM-based solution fine-tuned on an extensive real-world dataset for MDD diagnosis

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:53:12.327775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 65df63a0-1cf4-4166-b13e-a5ccea5486a9 · outbound

This paper cites Burden of disease scenarios for 204 countries and territories, 2022-2050: a forecasting analysis for the Global Burden of Disease Study.

MDD-LLM: Towards Accuracy Large Language Models for Major Depressive Disorder Diagnosis Burden of disease scenarios for 204 countries and territories, 2022-2050: a forecasting analysis for the Global Burden of Disease Study

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:53:12.297412Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 4a25c582-f286-440d-8f16-2fb517655a54 · outbound

This paper cites Bootstrap inference and machine learning reveal core differential plasma metabolic connectome signatures in major depressive disorder.

MDD-LLM: Towards Accuracy Large Language Models for Major Depressive Disorder Diagnosis Bootstrap inference and machine learning reveal core differential plasma metabolic connectome signatures in major depressive disorder

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:53:12.243166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 90cfecf4-539f-4dfb-9bcb-a8b7d7a73fc3 · outbound

This paper cites Prospective biomarkers of major depressive disorder: a systematic review and meta-analysis.

MDD-LLM: Towards Accuracy Large Language Models for Major Depressive Disorder Diagnosis Prospective biomarkers of major depressive disorder: a systematic review and meta-analysis

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:53:12.265932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation b72a80b9-e2c4-4905-93a3-37b84f0d1bb5 · outbound

This paper cites Predicting treatment response using EEG in major depressive disorder: A machine-learning meta-analysis.

MDD-LLM: Towards Accuracy Large Language Models for Major Depressive Disorder Diagnosis Predicting treatment response using EEG in major depressive disorder: A machine-learning meta-analysis

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:53:12.254885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 751311a8-dd1e-4ede-b325-e8effb89e276 · outbound

This paper cites Magnetic resonance imaging for individual prediction of treatment response in major depressive disorder: a systematic review and meta-analysis.

MDD-LLM: Towards Accuracy Large Language Models for Major Depressive Disorder Diagnosis Magnetic resonance imaging for individual prediction of treatment response in major depressive disorder: a systematic review and meta-analysis

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:53:12.231748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 4c27ff8c-fee7-4b32-a096-636d9049c1ff · outbound

This paper cites Automated accurate detection of depression using twin pascal’s triangles lattice pattern with eeg signals.

MDD-LLM: Towards Accuracy Large Language Models for Major Depressive Disorder Diagnosis Automated accurate detection of depression using twin pascal’s triangles lattice pattern with eeg signals

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:53:12.221151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 9793f334-5fa4-4475-9561-00215bd5c29e · outbound

This paper cites A textual-based featuring approach for depression detection using machine learning classifiers and social media texts.

MDD-LLM: Towards Accuracy Large Language Models for Major Depressive Disorder Diagnosis A textual-based featuring approach for depression detection using machine learning classifiers and social media texts

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:53:12.210704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 402a88dd-525e-4467-9e5a-db25a8f9957f · outbound

This paper cites Metabolic Connectome and Its Role in the Prediction, Diagnosis, and Treatment of Complex Diseases.

MDD-LLM: Towards Accuracy Large Language Models for Major Depressive Disorder Diagnosis Metabolic Connectome and Its Role in the Prediction, Diagnosis, and Treatment of Complex Diseases

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:53:12.199606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 5a9a1c2f-582a-4180-893e-39f4cf2be914 · outbound

This paper cites Longitudinal pathways between childhood BMI, body dissatisfaction, and adolescent depression: an observational study using the UK Millenium Cohort Study.

MDD-LLM: Towards Accuracy Large Language Models for Major Depressive Disorder Diagnosis Longitudinal pathways between childhood BMI, body dissatisfaction, and adolescent depression: an observational study using the UK Millenium Cohort Study

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:53:12.188901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 4e441988-1b22-4b01-9d9a-0b67310d4726 · outbound

This paper cites Sympathetic and blood pressure reactivity in young adults with major depressive disorder.

MDD-LLM: Towards Accuracy Large Language Models for Major Depressive Disorder Diagnosis Sympathetic and blood pressure reactivity in young adults with major depressive disorder

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:53:12.177524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 2dda63e1-1d97-4a09-8c51-921250f9ee3f · outbound

This paper cites Role of age, gender and marital status in prognosis for adults with depression: An individual patient data meta-analysis.

MDD-LLM: Towards Accuracy Large Language Models for Major Depressive Disorder Diagnosis Role of age, gender and marital status in prognosis for adults with depression: An individual patient data meta-analysis

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:53:12.166010Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 4d8b763c-d1ac-4f93-8ca7-f45c2afe2fea · outbound

This paper cites Income inequality and depression: a systematic review and meta-analysis of the association and a scoping review of mechanisms.

MDD-LLM: Towards Accuracy Large Language Models for Major Depressive Disorder Diagnosis Income inequality and depression: a systematic review and meta-analysis of the association and a scoping review of mechanisms

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:53:12.155130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 8d16cf93-6478-48bd-880f-1c72933df99c · outbound

This paper cites Testing and Evaluation of Health Care Applications of Large Language Models: A Systematic Review.

MDD-LLM: Towards Accuracy Large Language Models for Major Depressive Disorder Diagnosis Testing and Evaluation of Health Care Applications of Large Language Models: A Systematic Review

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:53:12.143920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 8ddfc855-a987-4576-9dcf-c7187adfb8f6 · outbound

This paper cites Multimodal machine learning enables AI chatbot to diagnose ophthalmic diseases and provide high-quality medical responses.

MDD-LLM: Towards Accuracy Large Language Models for Major Depressive Disorder Diagnosis Multimodal machine learning enables AI chatbot to diagnose ophthalmic diseases and provide high-quality medical responses

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:53:12.133093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 7fbadf95-5cd7-4b14-aa58-2d5e9596dca6 · outbound

This paper cites Foundation models for generalist medical artificial intelligence.

MDD-LLM: Towards Accuracy Large Language Models for Major Depressive Disorder Diagnosis Foundation models for generalist medical artificial intelligence

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:53:12.121976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation d50ad6fb-b4d4-46b2-b06a-68332f57e180 · outbound

This paper cites MetDIT: transforming and analyzing clinical metabolomics data with convolutional neural networks.

MDD-LLM: Towards Accuracy Large Language Models for Major Depressive Disorder Diagnosis MetDIT: transforming and analyzing clinical metabolomics data with convolutional neural networks

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:53:12.111082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation b7e5ff2d-9f0d-45cc-a250-72987733182b · outbound

This paper cites A novel lightweight deep learning fall detection system based on global-local attention and channel feature augmentation.

MDD-LLM: Towards Accuracy Large Language Models for Major Depressive Disorder Diagnosis A novel lightweight deep learning fall detection system based on global-local attention and channel feature augmentation

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:53:12.099622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 877791ff-23e2-4348-babc-2262f5c4ad2c · outbound

This paper cites The UK Biobank resource with deep phenotyping and genomic data.

MDD-LLM: Towards Accuracy Large Language Models for Major Depressive Disorder Diagnosis The UK Biobank resource with deep phenotyping and genomic data

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:53:12.076949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation b4669e89-f119-4be1-b2bc-e1389e27d893 · outbound

This paper cites MedChatZH: A tuning LLM for traditional Chinese medicine consultations.

MDD-LLM: Towards Accuracy Large Language Models for Major Depressive Disorder Diagnosis MedChatZH: A tuning LLM for traditional Chinese medicine consultations

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:53:12.087957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation eddbfe46-ee7e-4454-aa8f-5ecac94831f2 · outbound

This paper cites The UK Biobank is a large-scale prospective cohort study that recruited over 500,000 individuals (aged 40-69) between 2006 and.

MDD-LLM: Towards Accuracy Large Language Models for Major Depressive Disorder Diagnosis The UK Biobank is a large-scale prospective cohort study that recruited over 500,000 individuals (aged 40-69) between 2006 and

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:53:12.337971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 8c93aefc-e915-40c8-a48d-f1bf3c98780f · outbound

This paper cites HerbMet: Enhancing metabolomics data analysis for accurate identification of Chinese herbal medicines using deep learning.

MDD-LLM: Towards Accuracy Large Language Models for Major Depressive Disorder Diagnosis HerbMet: Enhancing metabolomics data analysis for accurate identification of Chinese herbal medicines using deep learning

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:53:12.065298Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 5f5de3ef-6bc8-4fd9-8029-18100011006f · outbound

This paper cites QLoRA: Efficient Finetuning of Quantized LLMs.

MDD-LLM: Towards Accuracy Large Language Models for Major Depressive Disorder Diagnosis QLoRA: Efficient Finetuning of Quantized LLMs

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:53:12.053539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation fe3e3dc3-355a-48cb-b0da-2d2bff861aa7 · outbound

This paper cites Multiple imputation with multivariate imputation by chained equation (MICE) package.

MDD-LLM: Towards Accuracy Large Language Models for Major Depressive Disorder Diagnosis Multiple imputation with multivariate imputation by chained equation (MICE) package

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:53:12.039077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation bc9daa90-9436-4652-bd05-7bba8fe99193 · outbound

This paper cites MissForest--non-parametric missing value imputation for mixed-type data.

MDD-LLM: Towards Accuracy Large Language Models for Major Depressive Disorder Diagnosis MissForest--non-parametric missing value imputation for mixed-type data

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:53:12.024962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 6028b2d1-4855-4e40-9979-a1b7453680e8 · outbound

This paper cites M-MDD: A multi-task deep learning framework for major depressive disorder diagnosis using EEG.

MDD-LLM: Towards Accuracy Large Language Models for Major Depressive Disorder Diagnosis M-MDD: A multi-task deep learning framework for major depressive disorder diagnosis using EEG

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:53:12.012737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation c732dd09-f5ad-400f-850a-cd8c99d0e02c · outbound

This paper cites Harnessing multimodal approaches for depression detection using large language models and facial expressions.

MDD-LLM: Towards Accuracy Large Language Models for Major Depressive Disorder Diagnosis Harnessing multimodal approaches for depression detection using large language models and facial expressions

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:53:12.001028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 5e30a596-a374-4266-a20e-dba39fbeddc4 · outbound

This paper cites Collaborative Enhancement of Consistency and Accuracy in US Diagnosis of Thyroid Nodules Using Large Language Models.

MDD-LLM: Towards Accuracy Large Language Models for Major Depressive Disorder Diagnosis Collaborative Enhancement of Consistency and Accuracy in US Diagnosis of Thyroid Nodules Using Large Language Models

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:53:11.989948Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 2db835b4-c5df-45ce-9441-8d296b64610a · outbound

This paper cites Evaluation of GPT-4 for 10-year cardiovascular risk prediction: Insights from the UK Biobank and KoGES data.

MDD-LLM: Towards Accuracy Large Language Models for Major Depressive Disorder Diagnosis Evaluation of GPT-4 for 10-year cardiovascular risk prediction: Insights from the UK Biobank and KoGES data

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:53:11.977992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 45059e6b-3d48-4bf2-aba1-d24223266e08 · outbound

This paper cites 2024;403:2204–56.

MDD-LLM: Towards Accuracy Large Language Models for Major Depressive Disorder Diagnosis 2024;403:2204–56

Reference 2021

Resolution: parse uncertain; raw_fallback, observed 2026-08-16T05:53:12.287152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Pith citing papers

No inbound Pith citation observations are available.